Algorithm aversion in delegated investing

Maximilian Germann, Christoph Merkle*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

6 Citations (Scopus)
13 Downloads (Pure)

Abstract

The tendency of humans to shy away from using algorithms—even when algorithms observably outperform their human counterpart—has been referred to as algorithm aversion. We conduct an experiment with young adults to test for algorithm aversion in financial decision making. Participants acting as investors can tie their incentives to either a human fund manager or an investment algorithm. We find no sign of algorithm aversion: participants care about returns, but do not have strong preferences which financial intermediary obtains these returns. Contrary to what has been suggested, participants are neither quicker to lose confidence in the algorithm after seeing it err. However, we find that participants’ inability to separate skill and luck when evaluating intermediaries slows down their migration to the algorithm.

Original languageEnglish
JournalJournal of Business Economics
Volume93
Issue9
Pages (from-to)1691-1727
Number of pages37
ISSN0044-2372
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Algorithm aversion
  • Asset management
  • Delegated investment
  • Financial technology

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